TY  - JOUR
T1  - Analysis of Big Data of HCV Patients
AU - J. Alkhatib, Ahed AU - Khaleel, Sara 
JO  - Research Journal of Medical Sciences
VL  - 14
IS  - 3
SP  - 58
EP  - 61
PY  - 2020
DA  - 2001/08/19
SN  - 1815-9346
DO  - rjmsci.2020.58.61
UR  - https://makhillpublications.co/view-article.php?doi=rjmsci.2020.58.61
KW  - HCV
KW  -liver
KW  -jaundice
KW  -headache
KW  -nausea
KW  -big data
AB  - The present study aimed to analyze big data
posted on Kaggle about HCV infection and to find
correlations between demographic variables and clinical
variables related to HCV infection. The data posted on
Kaggle is a large data consisting of 1385 patients. Data
included some variables such as age, gender and Body
Mass Index (BMI). Clinical manifestations were also
included such as fever, jaundice, headache, nausea and
vomiting. Variables including laboratory findings
including white blood cells, red blood cells, platelets and
hemoglobin were also included. Various statistical
models were included such as descriptive statistics such
as frequencies, percentages, means, and standard
deviations. The correlations between study variable were
assed using Pearson correlation. Significance was
considered at α#0.05. Study findings showed that clinical
manifestations were reported by about 50% of patients.
The results reported some correlations between study
variables including positively significant correlations
between HB and BMI, nausea and vomiting. Also, there
were some negatively significant correlation between
jaundice and BMI and diarrhea and hemoglobin. Taken
together, we recommend future studies to investigate the
importance of such correlations.
ER  -